TY - JOUR AU - Vasarevicius, D. AU - Martavicius, R. AU - Pikutis, M. PY - 2012/12/10 Y2 - 2024/03/29 TI - Application of Artificial Neural Networks for Maximum Power Point Tracking of Photovoltaic Panels JF - Elektronika ir Elektrotechnika JA - ELEKTRON ELEKTROTECH VL - 18 IS - 10 SE - DO - 10.5755/j01.eee.18.10.3065 UR - https://eejournal.ktu.lt/index.php/elt/article/view/3065 SP - 65-68 AB - Maximum power point tracking technique for PV panels with support of online learning artificial neural network is offered. Mathematical model of the system is implemented in Matlab/Simulink environment. Maximum power point tracking is performed using <em>IncCond</em> algorithm and radial basis function artificial neural network. Several criteria for estimation of system performance were derived. It is shown that ANN can increase overall system efficiency by 10%.<p>DOI: <a href="http://dx.doi.org/10.5755/j01.eee.18.10.3065">http://dx.doi.org/10.5755/j01.eee.18.10.3065</a></p> ER -